Razvan Pascanu

According to our database1, Razvan Pascanu authored at least 37 papers between 2010 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2019
Distilling Policy Distillation.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Relational recurrent neural networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Progress & Compress: A scalable framework for continual learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Been There, Done That: Meta-Learning with Episodic Recall.
Proceedings of the 35th International Conference on Machine Learning, 2018

Mix & Match Agent Curricula for Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Memory-based Parameter Adaptation.
Proceedings of the 6th International Conference on Learning Representations, 2018

Model compression via distillation and quantization.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Visual Interaction Networks: Learning a Physics Simulator from Video.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Distral: Robust multitask reinforcement learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A simple neural network module for relational reasoning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Sobolev Training for Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Sharp Minima Can Generalize For Deep Nets.
Proceedings of the 34th International Conference on Machine Learning, 2017

Discovering objects and their relations from entangled scene representations.
Proceedings of the 5th International Conference on Learning Representations, 2017

Learning to Navigate in Complex Environments.
Proceedings of the 5th International Conference on Learning Representations, 2017

Metacontrol for Adaptive Imagination-Based Optimization.
Proceedings of the 5th International Conference on Learning Representations, 2017

Sim-to-Real Robot Learning from Pixels with Progressive Nets.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

2016
Policy Distillation.
Proceedings of the 4th International Conference on Learning Representations, 2016

Interaction Networks for Learning about Objects, Relations and Physics.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Natural Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Malware classification with recurrent networks.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

2014
Revisiting Natural Gradient for Deep Networks
Proceedings of the 2nd International Conference on Learning Representations, 2014

On the number of inference regions of deep feed forward networks with piece-wise linear activations.
Proceedings of the 2nd International Conference on Learning Representations, 2014

How to Construct Deep Recurrent Neural Networks.
Proceedings of the 2nd International Conference on Learning Representations, 2014

Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

On the Number of Linear Regions of Deep Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Natural Gradient Revisited
Proceedings of the 1st International Conference on Learning Representations, 2013

Metric-Free Natural Gradient for Joint-Training of Boltzmann Machines
Proceedings of the 1st International Conference on Learning Representations, 2013

On the difficulty of training recurrent neural networks.
Proceedings of the 30th International Conference on Machine Learning, 2013


Advances in optimizing recurrent networks.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Learning Algorithms for the Classification Restricted Boltzmann Machine.
J. Mach. Learn. Res., 2012

2011
Contextual tag inference.
TOMCCAP, 2011

A neurodynamical model for working memory.
Neural Networks, 2011

Deep Learners Benefit More from Out-of-Distribution Examples.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

2010
Extraction of quadrics from noisy point-clouds using a sensor noise model.
Proceedings of the IEEE International Conference on Robotics and Automation, 2010


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